There are cameras known in the related art, that have a blur correcting function for preventing an unsteady hand movement during a photographing operation from lowering the quality of the captured image. Blurring is corrected in such a camera by adopting one of the following two primary methods.
The first method is an optical blur correction method in which a vibration of the camera is detected by using a vibration detection sensor such as an angular velocity sensor or an acceleration sensor and a blur is corrected by driving an optical system such as a photographic lens or a variable apex-angle prism in correspondence to the extent of the detected vibration (see, for instance, Japanese Laid Open Patent Publication No. S61-240780).
The second method is an electronic blur correction method in which the extent of blur is determined based upon the difference between the captured image and a previous image having been stored in memory on a temporary basis and the blur is corrected when reading out the image (see, for instance, Japanese Laid Open Patent Publication No. S63-187883). Through either of these two methods, the blur is corrected in real-time when the image is photographed.
There is another technology known in the related art which is used as an alternative blur correction method to those described above, through which a degraded image is restored as a blur-free image, unaffected by any unsteady hand movement. For instance, Japanese Laid Open Patent Publication No. S62-127976 discloses a method in which degradation of an image caused by a vibration occurring during the photographing operation is expressed as a point spread function and the image is restored as a blur-free image based upon the point spread function. There is also a technology known in the related art adopted in conjunction with a camera equipped with a vibration detection means alone, through which hand movement information is recorded and a blur is corrected by executing image restoration processing based upon the information when reproducing the image (see, for instance, Japanese Laid Open Patent Publication No. H 6-276512).
A specific method adopted in the image restoration processing is now explained. The term “image restoration” refers to a restoration of a blurred image, achieved by processing the blurred image based upon blur-related information so as to obtain an image manifesting a lesser extent of blurring.
With (x, y) representing positional coordinates on an image plane, o(x, y) representing an image obtained without experiencing any vibration (hereafter referred to as a raw image), z (x, y) representing an image degraded due to vibration (hereafter referred to as a blurred image) and p(x, y) representing information of a point image having become spread due to vibration (hereafter referred to as a point spread function), o(x, y), z(x, y) and p(x, y) achieve a relationship expressed as follows;z(x, y)=o(x, y)*p(x, y,)  (1)In the expression above, “*” indicates a convolution (convoluted integration) arithmetic operation, which is expressed specifically as follows;z(x, y)=∫∫σ(x, y)p(x−x′, y−y′)dx′dy′  (2)When the relationship is transformed into a relationship in a spatial frequency (u, v) range through a Fourier transform, expressions (1) and (2) are rewritten as follows;Z(u, v)=O(u, v)·P(u, v)  (3)
Z(u, v), O(u, v) and P(u, v) respectively represent the spectrums of z(x, y), o(x, y) and p(x, y). In addition, P(u, v) in expression (3) is specifically referred to as a spatial frequency transfer function.
If the point-image function p(x, y) can be somehow ascertained in addition to the blurred image z (x, y), their spectrums can be computed and then the spectrum O(u, v) of the raw image can be computed by using the following expression (4), which is a modified form of expression (3).
                              O          ⁡                      (                          u              ,              v                        )                          =                              Z            ⁡                          (                              u                ,                v                            )                                            P            ⁡                          (                              u                ,                v                            )                                                          (        4        )            
1/P(u, v) in expression (4) is specifically referred to as an inverse filter. The raw image o(x, y) can be determined through an inverse Fourier transformation of the spectrum computed by using expression (4). FIGS. 6(a) to 6(c) and FIGS. 7(a) to 7(d) illustrate the image restoration executed in the related art.
In order to simplify the explanation, it is assumed that a uniform blur has occurred along a single axis (the X axis), as shown in FIG. 6(b).
FIG. 7(a) shows a section taken from the point spread function. The results of a Fourier transformation executed on this section in FIG. 7(a), which are shown in FIG. 7(b), constitute the spatial frequency transfer function of the blur shown in FIG. 6(a). This transfer function has characteristics of special interest in that it assumes the value 0 at a plurality of points. The inverse filter of this function manifests instances of infinity, as shown in FIG. 7(c). When the inverse filter is incorporated in expression (4), the phenomenon expressed as in (5) below occurs with regard to a specific spatial frequency and, in such a case, the spectrum value of the raw image is indeterminate.
                              O          ⁡                      (                          u              ,              v                        )                          =                                            Z              ⁡                              (                                  u                  ,                  v                                )                                                    P              ⁡                              (                                  u                  ,                  v                                )                                              =                                    0              0                        =            indeterminate                                              (        5        )            
When the transfer function indicates the value 0, there is a frequency component that has not been transferred in the case of a blur (information has been lost), and accordingly, the expression above indicates that the lost frequency component cannot be restored. This, in turn, means that the complete recovery of the raw image is not possible.
It is to be noted that a Wiener filter expressed as below is actually used in the image restoration so as to ensure that the inverse filter does not manifest infinity.
                                          P            *                          (                              u                ,                v                            )                                                                                                            P                  ⁡                                      (                                          u                      ,                      v                                        )                                                                              2                        +                          1              /              c                                      ⁢                                  ⁢        C        ⁢                  :                ⁢                                  ⁢        constant                            (        6        )            
FIG. 7(d) is a graph of the Wiener filter.
The use of the Wiener filter ensures that O(u, v) is not allowed to become indeterminate, unlike in expression (5).
However, the following problems exist in the optical blur correction and the image restoration in the related art described above.